yiling-j / cacheme

Asyncio cache framework for Python

Hi there 👋

• 🔭 I’m currently working on Tablesmith, a privacy-first, cross platform spreadsheet ETL app

cacheme's Issues

type safe and elegent decorator

With the help of type hints it's possible to limit key function's signature, just the same way as Cacheme. Using a separate function avoids the weird lamda or f-string in original decorator

@Cache("tlfu", 10000)
async def get_user_info(user_id: int) -> Dict:
    return {}

# or use existing cache
cache = Cache("tlfu", 10000)
@cache
async def get_user_info(user_id: int) -> Dict:
    return {}

# register key function: function name is not important, so just use _ here
@get_user_info.key
def _(user_id: int) -> str:
    return f"user:{user_id}"

V2

Based on the experience of cacheme-go, proposal following improvements:

• enforce schema/node
• typing/asyncio support
• multiple storages(redis/sql databases)
• multiple serializers(pickle/json/msgpack)
• local cache support
• prometheus integration
• API and admin page

Limit meta keys size

Meta keys just store set of key names, for example, delete meta key set stores deleted key names. Becasue key names are always short string, to make use of hash-max-ziplist-entries and save some memory, we can just bucket key name, just as instagram do Storing hundreds of millions of simple key-value pairs in Redis.

My idea is add some options to node or node fields, so we can dynamically bucket node keys. Each node will has its own meta keys namespace, and depend on node fields, we calculate the meta key info.
Or maybe hash the key and use bitmap to store those info.

Improvements

• Support invalid single key in node
• Add class META to node, then we can put attributes there, for example timeout
• Add stale option to global settings, also decorator and node
• Add capability to define functions in node(hit/skip...)
• Refactor code

Support compress option

Add option in settings to enable compress for value byte size larger than given threshold

Better way to set key

Now I use string to set key in decorator, this is not easy for management, also user may have typos. So separate keys into a new python file, make them class, and just import in decorator maybe a better choice

reduce overhead

Currently Cacheme overhead is too high, the local storage performance is much worse than native Theine API, need to improve: 1. try replace async event with awaitable, 2. optimize get/get_many, simplify code